区域PM2.5时空回归建模与预测

基于区域PM_(2.5)时空建模和预测的需要及PM_(2.5)浓度呈现明显的时空分布趋势的状况,以苏南地区2014年PM_(2.5)日监测数据为实验数据,使用回归克里格对区域PM_(2.5)进行时空建模和估值。利用最小二乘法建立了PM_(2.5)与时空位置的三元二次回归趋势模型,建模点趋势值与实测值间的平均误差接近于0,表明趋势模型拟合效果较好;拟合了样点残差的理论变异函数模型,表明该地区PM_(2.5)的空间和时间相关性范围分别为150 km和4 d;基于该模型,使用时空普通克里格对残差进行时空插值;插值结果与趋势项相加,得到PM_(2.5)回归克里格估值结果;通过对比不考虑趋势的时空普通克里格估值结果,发现考虑时空趋势的时空回归克里格法精度提高了1. 29%。对所提方法进行了创新性分析,并对不足之处进行了讨论。     

基于时空回归克里格和AOD数据的PM2.5时空插值

基于京津冀地区2016年PM_(2.5)浓度监测数据和MOD04的10 km分辨率气溶胶数据,结合时空位置,建立PM_(2.5)回归模型,使用时空回归克里格方法对京津冀地区进行PM_(2.5)时空插值,对比研究时空回归克里格与只使用监测站数据的普通时空克里格方法的时空插值结果。结果表明,两种方法的插值结果时空趋势相同,京津冀地区东南部PM_(2.5)浓度较高,夏秋两季浓度低于春冬两季;时空回归克里格插值结果的均方根误差为26.1,时空克里格插值结果均方根误差为28.3,即兼顾时空趋势并结合气溶胶数据的时空回归克里格插值精度提高了约8%。     

山区土壤重金属空间插值性能的改进

山区土壤重金属监测中,密集均匀的布点采样困难大,成本高。根据稀疏非均匀样本数据准确预测山区土壤重金属空间分布,对可视化描述检测元素的分布及趋势具有重要意义。基于云南省楚雄市南部山区表层土壤中重金属锰、钒的采样数据,对集成径向基函数神经网络(IRBFANNs)和传统插值方法:反距离(IDW)、普通克里格(OK)、径向基函数神经网络(RBFANNs),进行了不同等级采样密度下的插值性能比较。结果表明,样本点数量减少时,传统预测方法的插值精度都有所下降,而IRBFANNs算法在样本点较少情况下能够保持最好的插值精确度和稳定性,有效改进了空间插值性能。     

灵宝市金矿选冶区土壤汞的地统计分析及污染评价

利用数理统计、地统计方法和地理信息系统(GIS)技术研究了灵宝市的金矿选冶区土壤汞的空间分布特性和污染程度评价。Hg和Cu、Zn、Pb、Cd重金属元素存在较大的偏度和峰度,为了使这些元素的数据服从正态分布并降低其偏度和峰度,采用了Box-Cox变换。地统计分析认为研究区内土壤Hg元素具有空间结构特性。用普通克里格插值绘制的研究区Hg含量地球化学图体现了其空间分布特征。结合地累积指数法评价指标得出的研究区Hg污染等级分布图为土壤恢复治理提供了一定科学依据。     

新疆气候暖湿化背景下干旱分布与演变特征

新疆是我国降水最少、产水能力最低的地区，自然灾害主要是干旱。本文基于实测降水、径流数据，依据全国第三次水资源调查评价形成的新疆降水、径流等值线图，形成干旱分布图，并构建年尺度面降水、径流系列。采用干旱分布图和系列数据，按不同空间尺度量化分析了研究区干旱状态和演变规律。新疆多年平均降水深为157.7 mm,单位面积产水量48.5 mm, 80%以上的面积属干旱、半干旱区，南疆较北疆干旱、山区相对湿润、平原干旱。在气候变暖的背景下，呈现不同程度湿化趋势，但气象干旱和水文干旱的气候形态并未发生改变。近30 a的相对丰水期，由于经济社会用水量的不断增加，加之高温导致的径流年际波动加剧，使新疆面临更为严峻的干旱形势。     

2008—2019年黑龙江省酸雨特征分析

采用统计分析与空间插值等方法对黑龙江省16个酸雨监测站2008—2019年的酸雨观测数据统计计算,分析该省酸雨变化特征和影响因素。结果表明：12 a间黑龙江省秋冬季在pH值＜5.60条件下酸雨频率均值达到15.6%,维持在较高水平;相关性分析显示,在pH值＜5.00条件下年均降水pH值与酸雨频率的相关系数为-0.83,呈强负相关性;虽然有效降水量是酸雨产生的前提条件,但年有效降水量与pH值相关性不明显,平均电导率与年均有效降水量的相关系数达到-0.80,降水量对电导率有较强的抑制作用;空间分布显示,在pH值＜5.60和＜5.00条件下的酸雨频率分别为20%～55%和10%～35%,酸雨频率高值区与pH低值区分布趋于一致。     

气候变化下的新疆生态环境脆弱性评价

选取了脆弱性、适应能力作为影响新疆生态环境脆弱性的条件层，进一步筛选出海拔、地质环境、沙尘暴、人口密度、降水量、植被类型、生态保护政策7个因子作为成因指标层，并用专家打分法对每个指标赋予权重。将研究区剖分成195个评价单元格，借助G玛强大的数据管理功能，建立与空间数据和属性数据相互关联的生态环境脆弱性数据库；首次采用模糊数学层次分析法作为新疆生态环境脆弱性等级计算的数学模型，计算出新疆生态环境脆弱性等级，并借助CIS进行成果表达。     

乌鲁木齐市近年来大气降尘变化规律及空间分布特征

基于乌鲁木齐市多年监测的降尘数据,对乌鲁木齐市城区的降尘量进行了统计分析,得出了乌鲁木齐市近10年来降尘的总体变化规律;利用方差分析方法检验了不同季节降尘的显著性差异,发现采暖期的降尘量明显大于非采暖期;按行政区分析降尘量的分布变化,结果为不同行政区存在差别;利用秩相关系数法对其进行了趋势分析。结果表明,乌鲁木齐市的降尘呈下降趋势。利用Arc GIS9.3中的普通克里格插值方法绘制了乌鲁木齐市城市自然降尘的空间分布图。     

克拉玛依市大气降水化学的统计学分析

运用相关分析、因子分析和聚类分析等统计学分析方法,对2009—2010年新疆克拉玛依市的大气降水化学组成和分布特征进行分析。结果表明,SO4^2-、Cl^-、Ca^2＋和Na^＋是降水中主要离子。降水的pH值、电导率、降水量和各离子组份均呈现明显的正偏态分布,降水样品以低离子含量的样本为主,因子分析和聚类分析2种分类方法分析降水中水溶性离子主要分为3类。SO4^2-、Cl^-、Mg^2＋、F^-主要来自人为活动的贡献,K^＋、Ca^2＋主要来源于土壤和沙尘等地壳,H^＋与其他阴、阳离子间并未表现出明显的相关关系,表明研究区域的降水酸度是所有致酸离子和各种离子综合作用的结果,而不是降水中某个单一的离子组份确定的。     

校园降水资源利用探讨

针对石河子大学降水资源利用问题,开展了大学校区降水水质监测分析。通过对校区内天然降水p H、NH3、CODCr、SS的检测,与城市杂用水水质标准(GB/T 18920-2002)及城市污水再生利用——景观用水水质(GB/T 18921-2002)中的相关参数进行比较,得出天然降水经过处理具有作为城市绿化、冲厕、道路清扫、消防、车辆冲洗用水及观赏性景观水景类环境用水潜能。同时得出石河子大学的降水具有资源利用的潜力。     

1976-2005年唐山地区降水变化规律及干旱预测

利用唐山市1976-2005年各县年降水序列，分析了该市降水的空间分布规律和时间变化特点。采用灰色系统的灾变预测方法，对各县分别建立了GM（1，1）模型，进行未来25年唐山市各站的干旱年预测。利用残差检验、后验差检验和关联度检验对各模型分别进行了精度检验。结果表明，预测模型精度较高，可以对唐山市各县未来的干旱年进行预测，从而为科学决策提供依据。     

Kriging and Bilinear Methods for Estimating Spatial Pattern of Atmospheric Pollutants

Two statistical methods to reconstruct the spatial pattern ofenvironmental data are compared: the Kriging and the Bilinear.The comparison is performed by evaluating two differentcharacteristics of the methods: the interpolation and the estimation. The Kriging method is demonstrated to be better thanthe Bilinear regarding all the statistics studied, although thedifferences are not very significant. Especially, the Kriging ismore efficient than the Bilinear in the reconstruction of peakvalues and it does not extrapolate local trends. The methods areapplied to a set of environmental data measured in an urban area.     

基于GIS空间插值方法的长湖水质评价

通过对各插值方法选择后取反距离加权法与克立格法对长湖的污染现状进行分析,结果表明大部分水域水质处于Ⅴ类和劣Ⅴ类,只有主要出水口习家口和刘岺闸附近的部分水域的水质可以达到Ⅳ类水质标准.同时发现反距离加权法与克立格法均具有较高的精度,但克立格法优于反距离加权法,这两种方法评价湖泊水质都能取得比较好的效果.     

Optimal extension of the rain gauge monitoring network of the Apulian Regional Consortium for Crop Protection

The goal of this paper is to provide a methodology for assessing the optimal localization of new monitoring stations within an existing rain gauge monitoring network. The methodology presented, which uses geostatistics and probabilistic techniques (simulated annealing) combined with GIS instruments, could be extremely useful in any area where an extension of whatever existing environmental monitoring network is planned. The methodology has been applied to the design of an extension to a rainfall monitoring network in the Apulia region (South Italy). The considered monitoring network is managed by the Apulian Regional Consortium for Crop Protection (ARCCP), and, currently consists of 45 gauging stations distributed over the regional territory, mainly located on the basis of administrative needs. Fifty new stations have been added to the existing monitoring network, split in two groups: 15 fixed and 35 mobile stations. Two different methods were applied and tested: the Minimization of the Mean of Shortest Distances method (MMSD) and Ordinary Kriging (OK) whose related objective function is estimation variance. The MMSD, being a purely geometric method, produced a spatially uniform configuration of the gauging stations. On the contrary, the approach based on the minimization of the average of the kriging estimation variances, produced a less regular configuration, though a more reliable one from a spatial standpoint. Nevertheless, the MMSD approach was chosen, since the ARCCP's intention was to create a new monitoring network characterized by uniform spatial distribution throughout the regional territory. This was the most important constraint given to the project by the ARCCP, whose main objective was to accomplish a territorial network capable of detecting hazardous events quickly. A seasonal aggregation of the available rainfall data was considered. The choice of the temporal aggregation in quarterly averages allowed four different optimal configurations to be determined per season. The overlapping of the four configurations allowed a number of new station locations, which tended to remain fixed season after season, to be identified. Other stations, instead, changed their coordinates considerably over the four seasons. Constraints were defined in order to avoid placing new monitoring locations either near existing stations, belonging to other Agencies, or near the coast line.     

GIS技术在东昌湖水质评价中的应用

利用GPS定位对东昌湖进行水样采集,把水质数据和坐标联系在一起,测定的结果利用GIS技术进行克里格插值.在用一部分数据验证其准确性之后,把全部水质数据以图的形式呈现出来,进行分析评价,通过与湖泊营养类型标准对比得出东昌湖大部分湖区出现富营养化现象,污染严重.证明GIS技术可以很好地应用于湖泊水质研究.     

Geostatistical Evaluation of Spatial Variation Related to Groundwater Quality Database: Case Study for Arak Plain Aquifer,Iran

Geostatistical methods are one of the advanced techniques to interpolate groundwater quality data. Geostatistical interpolation techniques employ both the mathematical and the statistical properties of the measured points. Compiling the data distribution on spatial and temporal domain is of crucial importance in order to evaluate its quality and safety. The main purpose of this paper is to assess groundwater quality of Arak plain, Iran, by an unbiased interpolated method so called Kriging. Therefore, seven quality variables of Arak plain aquifer including TDS, SAR, EC, Na⁺, TH, Cl^?, and SO₄ ^2? have been analyzed, studied, and interpreted statistically and geostatistically. Utilized data in this study were collected from 97 water well samples in Arak plain, in 2012. After normalizing data, variogram as a geostatistical tool for defining spatial regression was calculated and experimental variograms have been plotted by GS⁺ software, then the best theoretical model was fitted to each variogram based on minimum RSS error. Cross validation was used to determine the accuracy of the estimated data. The uncertainty of the method could be well assessed via this method since the method not only gave the average error (around 0 in this study) but also gave the standard deviation of the estimations. Therefore, more than 3800 points were estimated by ordinary Kriging algorithm in places which have not been sampled. Finally, estimation maps of groundwater quality were prepared and map of estimation variance, EV, has been presented to assess the quality of estimation in each estimated point. Results showed that the Kriging method is more accurate than the traditional interpolation algorithms not honoring the spatial properties of the database.     

2010-2015年昌吉市大气降水离子特征变化趋势研究

依据昌吉州环境监测站2010—2015年降水监测资料，分析昌吉地区降水中离子特征及变化趋势，阐明昌吉市降水污染现状及变化特征。结合昌吉市特有的气象条件、地形地貌和工业分布情况，分析污染物来源及污染变化趋势。     

Improved mapping of National Atmospheric Deposition Program wet-deposition in complex terrain using PRISM-gridded data sets

High-elevation regions in the United States lack detailed atmospheric wet-deposition data. The National Atmospheric Deposition Program/National Trends Network (NADP/NTN) measures and reports precipitation amounts and chemical constituent concentration and deposition data for the United States on annual isopleth maps using inverse distance weighted (IDW) interpolation methods. This interpolation for unsampled areas does not account for topographic influences. Therefore, NADP/NTN isopleth maps lack detail and potentially underestimate wet deposition in high-elevation regions. The NADP/NTN wet-deposition maps may be improved using precipitation grids generated by other networks. The Parameter-elevation Regressions on Independent Slopes Model (PRISM) produces digital grids of precipitation estimates from many precipitation-monitoring networks and incorporates influences of topographical and geographical features. Because NADP/NTN ion concentrations do not vary with elevation as much as precipitation depths, PRISM is used with unadjusted NADP/NTN data in this paper to calculate ion wet deposition in complex terrain to yield more accurate and detailed isopleth deposition maps in complex terrain. PRISM precipitation estimates generally exceed NADP/NTN precipitation estimates for coastal and mountainous regions in the western United States. NADP/NTN precipitation estimates generally exceed PRISM precipitation estimates for leeward mountainous regions in Washington, Oregon, and Nevada, where abrupt changes in precipitation depths induced by topography are not depicted by IDW interpolation. PRISM-based deposition estimates for nitrate can exceed NADP/NTN estimates by more than 100% for mountainous regions in the western United States.     

Spatial variability of air pollutants in the city of Taranto, Italy and its potential impact on exposure assessment

Epidemiological studies typically use monitored air pollution data from a single station or as averaged data from several stations to estimate population exposure. In industrialized urban areas, this approach may present critical issues due to the spatial complexities of air pollutants which are emitted by different sources. This study focused on the city of Taranto, which is one of the most highly industrialized cities in southern Italy. Epidemiological studies have revealed several critical situations in this area, in terms of mortality excess and short-term health effects of air pollution. The aims of this paper are to study the variability of air pollutants in the city of Taranto and to interpret the results in relation to the applicability of the data in assessing population exposure. Meteorological and pollution data (SO2, NO2, PM10), measured simultaneously and continuously during the period 2006–2010 in five air quality stations, were analyzed. Relative and absolute spatial concentration variations were investigated by means of statistical indexes. Results show significant differences among stations. The highest correlation between stations was observed for PM10 concentrations, while critical values were found for NO2. The worst values were observed for the SO2 series. The high values of 90th percentile of differences between pairs of monitoring sites for the three pollutants index suggest that mean concentrations differ by large amounts from site to site. The overall analysis supports the hypothesis that various parts of the city are differently affected by the different emission sources, depending on meteorological conditions. In particular, analysis revealed that the influence of the industrial site may be primarily identified with the series of SO2 data which exhibit higher mean concentration values and positive correlations with wind intensity when the monitoring station is downwind from the industrial site. Results suggest evaluating the population exposure to air pollutants in industrialized cities by taking into account the possible zones of influence of different emission sources. More research is needed to identify an indicator, which ought to be a synthesis of several pollutants, and take into account the meteorological variables.